#region License Information /* HeuristicLab * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Parameters; using HeuristicLab.Selection; namespace HeuristicLab.Algorithms.NSGA2 { public class RankAndCrowdingSorter : AlgorithmOperator { public ValueLookupParameter MaximizationParameter { get { return (ValueLookupParameter)Parameters["Maximization"]; } } public ScopeTreeLookupParameter QualitiesParameter { get { return (ScopeTreeLookupParameter)Parameters["Qualities"]; } } public ScopeTreeLookupParameter RankParameter { get { return (ScopeTreeLookupParameter)Parameters["Rank"]; } } public ScopeTreeLookupParameter CrowdingDistanceParameter { get { return (ScopeTreeLookupParameter)Parameters["CrowdingDistance"]; } } public RankAndCrowdingSorter() : base() { Parameters.Add(new ValueLookupParameter("Maximization", "For each objective a value that is true if that objective should be maximized, or false if it should be minimized.")); Parameters.Add(new ScopeTreeLookupParameter("Qualities", "The vector of quality values.")); Parameters.Add(new ScopeTreeLookupParameter("Rank", "The rank of a solution (to which front it belongs).")); Parameters.Add(new ScopeTreeLookupParameter("CrowdingDistance", "The crowding distance of a solution in a population.")); FastNonDominatedSort fastNonDominatedSort = new FastNonDominatedSort(); UniformSubScopesProcessor subScopesProcessor = new UniformSubScopesProcessor(); CrowdingDistanceAssignment crowdingDistanceAssignment = new CrowdingDistanceAssignment(); CrowdedComparisonSorter crowdedComparisonSorter = new CrowdedComparisonSorter(); MergingReducer mergingReducer = new MergingReducer(); fastNonDominatedSort.MaximizationParameter.ActualName = MaximizationParameter.Name; fastNonDominatedSort.QualitiesParameter.ActualName = QualitiesParameter.Name; fastNonDominatedSort.RankParameter.ActualName = RankParameter.Name; crowdingDistanceAssignment.CrowdingDistanceParameter.ActualName = CrowdingDistanceParameter.Name; crowdingDistanceAssignment.QualitiesParameter.ActualName = QualitiesParameter.Name; crowdedComparisonSorter.CrowdingDistanceParameter.ActualName = CrowdingDistanceParameter.Name; crowdedComparisonSorter.RankParameter.ActualName = RankParameter.Name; OperatorGraph.InitialOperator = fastNonDominatedSort; fastNonDominatedSort.Successor = subScopesProcessor; subScopesProcessor.Operator = crowdingDistanceAssignment; crowdingDistanceAssignment.Successor = crowdedComparisonSorter; crowdedComparisonSorter.Successor = null; subScopesProcessor.Successor = mergingReducer; mergingReducer.Successor = null; } } }